Computer vision is a field of artificial intelligence (AI) that enables computers to interpret and analyze the visual world, simulating the way humans see and understand their environment. It involves the development of automated systems that can interpret visual data, such as photographs or motion pictures, in the same manner as people do. Computer vision applies machine learning models to identify and classify objects in digital images and videos, then lets computers react to what they see. Some key features of computer vision include:
-
Image recognition: This involves identifying and classifying objects in digital images and videos.
-
Object detection: This involves detecting the presence and location of objects in digital images and videos.
-
Facial recognition: This involves identifying and verifying the identity of individuals based on their facial features.
-
Edge detection: This involves identifying the boundaries between objects in digital images and videos.
-
Pattern detection: This involves identifying patterns in digital images and videos.
-
Image segmentation: This involves dividing digital images into segments or regions based on their visual characteristics.
Computer vision is used in a wide range of industries, including manufacturing, automotive, healthcare, and security. It enables self-driving cars to safely navigate streets and highways, allows facial recognition tools to match images of peoples faces to their identities, and enables augmented-reality applications to mix virtual objects with real-world images. Computer vision applications are used to improve the consumer experience, reduce costs, and tighten security. Manufacturers use it to spot defective products on the assembly line and prevent them from shipping to customers, while medical professionals use it to scan X-rays, MRIs, and ultrasounds to detect health problems. Computer vision needs lots of data, and it runs analyses of data over and over until it discerns distinctions and ultimately recognizes images. Two essential technologies used to accomplish this are deep learning and convolutional neural networks (CNN).
